This invention relates, in general, to feedback control systems and, more specifically, to adaptive control systems using mathematical system models.
The control of certain system variables and their derivatives, such as position and velocity, of a dynamic system is required in various applications. Variations in the characteristics of the system being controlled and changes in external conditions complicates the control requirements in many cases. High speed military aircraft, missiles, motor drives, chemical plants, rolling mills, and voltage regulators are a few examples of applications where a system output must be maintained in the presence of changing dynamic characteristics, such as wind, terrain, frequency, voltage, inertia, component aging, loading, and temperature. The present invention describes the automatic generation of the input signals to the controlled system by means of predictive and model reference adaptive control techniques. This combined technique makes the controlled system perform much more accurately and consistently than conventional techniques when the system characteristics vary rapidly and drastically due to external disturbances and changing conditions as the system is operating.
Conventional controllers known in the prior art include predictive controllers and model reference adaptive controllers. Predictive control is a method or system for making the output of the controlled system follow a desired trajectory, or value, with much less following error than is usually possible with simple error feedback control systems. In predictive control, the input to the system is varied according to an impulse, or step, response model of the system in such a manner as to cause the output of both the model and the controlled system to follow the prescribed trajectory. The predictive technique looks into the future to determine what the actual system output will be at some later time. This is accomplished by applying present and future inputs to the impulse model of the system. By use of multi-input, multi-output models, cross coupling between axes or processes can also be greatly reduced with predictive control.
Model reference adaptive control (MRAC) consists of a reference model, chosen at the discretion of the designer, which provides an effective and flexible means of specifying desired closed-loop performance characteristics. The parameters of the controller, or the feedback gains, are adjusted in such a way that the errors between the reference model output and the actual system output are minimized. The objective of MRAC is to force the output of the system and its derivatives to be the same as that of the mathematical reference model. The reference model has dynamic characteristics which do not change as the system operates. The actual controlled system, with its changing characteristics, is forced to attain the unchanging characteristics of the model by means of the adaptive control technique. Background material in MRAC techniques is contained in "Comparative Studies of Model Reference Adaptive Control Systems," by Hang and Parks, IEEE Transactions on Automatic Control, Vol. AC-18, No. 5, October, 1973. However, MRAC systems do not have the capability of following a desired input trajectory with a potentially zero following error.
Conventional predictive controllers use an "identifier" to determine the matchematical relationship of the system impulse response model so that the predictive control technique will work properly when used with systems having dynamic characteristics which change while they are operating. If the system model dynamics exactly match those of the controlled system, the input predictor will provide inputs to the system which cause the system output to follow exactly the desired trajectory without any lag error, provided that the trajectory to be followed does not require the system to exceed its power capabilities. The identifier requires a certain amount of computational time to update the model weights. In general, higher processing speeds of the controller result in better following accuracy of the desired trajectory, and in less likelihood of undesirable instability which can be induced by the computational time delays inherent in the use of an identifier.
Determining the proper inputs to the dynamic system being controlled as quickly, accurately, and efficiently as possible is the main objective of this and most trajectory controllers. Therefore, it is desirable, and it is an object of this invention, to provide a controller which exhibits the advantages of both predictive and model references adaptive controllers without some of the undesirable characteristics of either system operating independently.